利用小波神经网络对航空光纤极化状态变化进行天气适应性多步骤预测

arXiv - CS - Networking and Internet Architecture Pub Date : 2024-09-05 DOI:arxiv-2409.03663

Khouloud Abdelli, Matteo Lonardi, Jurgen Gripp, Samuel Olsson Fabien Boitier, Patricia Layec

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引用次数: 0

摘要

我们介绍了一种新颖的天气适应方法，用于对空中光纤链路中的多尺度 SOP 变化进行多步骤预测。通过利用离散小波变换并结合天气数据，与基线相比，我们的方法在 RMSE 和 MAPE 方面分别提高了 65% 和 63% 以上的预测精度。

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Weather-Adaptive Multi-Step Forecasting of State of Polarization Changes in Aerial Fibers Using Wavelet Neural Networks

We introduce a novel weather-adaptive approach for multi-step forecasting of multi-scale SOP changes in aerial fiber links. By harnessing the discrete wavelet transform and incorporating weather data, our approach improves forecasting accuracy by over 65% in RMSE and 63% in MAPE compared to baselines.

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arXiv - CS - Networking and Internet Architecture

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